مقایسهٔ روشها
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| تقریب بورن-اوپنهایمر× | الگوریتم خودکار مقادیر ویژه متغیر× | |
|---|---|---|
| حوزه | محاسبات کوانتومی | محاسبات کوانتومی |
| خانواده | Machine learning | Machine learning |
| سال پیدایش≠ | 1927 | 2014 |
| پدیدآور≠ | Max Born and Julius Robert Oppenheimer | Alberto Peruzzo |
| نوع≠ | Fundamental approximation | Hybrid quantum-classical algorithm |
| منبع بنیادین≠ | Born, M., Oppenheimer, J. R. (1927). Zur Quantentheorie der Moleküle. Annalen der Physik, 84, 457–484. DOI ↗ | Peruzzo, A., McClean, J., Shadbolt, P., et al. (2014). A variational eigenvalue solver on a photonic quantum processor. Nature Communications, 5, 4213. DOI ↗ |
| نامهای دیگر | BO approximation, clamped nuclei | VQE, hybrid quantum-classical |
| مرتبط≠ | 3 | 4 |
| خلاصه≠ | The Born-Oppenheimer (BO) Approximation is a foundational assumption in molecular quantum mechanics that nuclei can be treated as fixed while solving for electrons, and vice versa. Introduced by Born and Oppenheimer in 1927, this separation reduces the complex many-body electronic-nuclear problem to a sequence of simpler problems, enabling nearly all molecular calculations. | The Variational Quantum Eigensolver (VQE) is a hybrid quantum-classical algorithm designed to find the lowest eigenvalue (ground state energy) of a quantum Hamiltonian. Introduced by Peruzzo et al. in 2014, it exploits the variational principle to combine the power of quantum circuits with classical optimization to solve chemistry and materials science problems on near-term quantum devices. |
| ScholarGateمجموعهداده ↗ |
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